A robust salient object detection using edge enhanced global topographical saliency

Singh, Surya Kant; Srivastava, Rajeev

doi:10.1007/s11042-020-08644-9

Cited by 8 publications

(1 citation statement)

References 46 publications

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“…Our SoD-Net HDR-IW method is implemented in Matlab 2020 (Windows 10) running on a PC with an AMD Ryzen 5 3500U, Radeon Vega Gfx, and 16GB-RAM. For experiment and comparison purposes, we used the RIT-MCSL [22] and MSRA datasets 1 [24]. Additionally, we set the background to be slightly hazy (α = 0.04) and salient object to be entirely invisible (β = 0.02).…”

Section: Experiments and Resultsmentioning

confidence: 99%

HDR image watermarking using saliency detection and quantization index modulation

Ahmed¹,

Kuribayashi²,

Wong³

et al. 2023

Preprint

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High-dynamic range (HDR) images are circulated rapidly over the internet with risks of being exploited for unauthorized usage. To protect these images, some HDR imagebased watermarking (HDR-IW) methods were put forward. However, they inherited the same problem faced by conventional IW methods for standard dynamic range (SDR) images, where only trade-offs among conflicting requirements are managed instead of simultaneous improvement. In this paper, a novel saliency (eye-catching object) detection based trade-off independent HDR-IW is proposed, to simultaneously improve robustness, imperceptibility and payload. First, the host image goes through our proposed salient object detection model to produce a saliency map, which is, in turn, exploited to segment the foreground and background of the host image. Next, the binary watermark is partitioned into the foregrounds and backgrounds using the same mask and scrambled using a random permutation algorithm. Finally, the watermark segments are embedded into selected bit-plane of the corresponding host segments using quantized indexed modulation. Experimental results suggest that the proposed work outperforms state-of-the-art methods in terms of improving the conflicting requirements.

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Section: Experiments and Resultsmentioning

confidence: 99%

HDR image watermarking using saliency detection and quantization index modulation

Ahmed¹,

Kuribayashi²,

Wong³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

High payload watermarking based on enhanced image saliency detection

Khan

Wong

2022

Multimed Tools Appl

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Nowadays, images are circulated rapidly over the internet and they are subject to some risk of misuses. To address this issue, various watermarking methods are proposed in the literature. However, most conventional methods achieve a certain trade-off among imperceptibility and high capacity payload, and they are not able to improve these criteria simultaneously. Therefore, in this paper, a robust saliency-based image watermarking method is proposed to achieve high payload and high quality watermarked image. First, an enhanced salient object model is proposed to produce a saliency map, followed by a binary mask to segments the foreground/background region of a host image. The same mask is then consulted to decompose the watermark image. Next, the RGB channels of the watermark are encrypted by using Arnold, 3-DES and multi-flipping permutation encoding (MFPE). Furthermore, the principal key used for encryption is embedded in the singular matrix of the blue channel. Moreover, the blue channel is encrypted by using the Okamoto-Uchiyama homomorphic encryption (OUHE) method. Finally, these encrypted watermark channels are diffused and embedded into the host channels. When the need arises, more watermarks can be embedded into the host at the expense of the quality of the embedded watermarks. Our method can embed watermark of the same dimension as the host image, which is the first of its kind. Experimental results suggest that the proposed method maintains robustness while achieving high image quality and high payload. It also outperforms the state-of-the-art (SOTA) methods.

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Trade-off independent image watermarking using enhanced structured matrix decomposition

Khan,

Wong,

Baskaran

2024

Multimed Tools Appl

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Image watermarking plays a vital role in providing protection from copyright violation. However, conventional watermarking techniques typically exhibit trade-offs in terms of image quality, robustness and capacity constrains. More often than not, these techniques optimize on one constrain while settling with the two other constraints. Therefore, in this paper, an enhanced saliency detection based watermarking method is proposed to simultaneously improve quality, capacity, and robustness. First, the enhanced structured matrix decomposition (E-SMD) is proposed to extract salient regions in the host image for producing a saliency mask. This mask is then applied to partition the foreground and background of the host and watermark images. Subsequently, the watermark (with the same dimension of host image) is shuffled using multiple Arnold and Logistic chaotic maps, and the resulting shuffled-watermark is embedded into the wavelet domain of the host image. Furthermore, a filtering operation is put forward to estimate the original host image so that the proposed watermarking method can also operate in blind mode. In the best case scenario, we could embed a 24-bit image as the watermark into another 24-bit image while maintaining an average SSIM of 0.9999 and achieving high robustness against commonly applied watermark attacks. Furthermore, as per our best knowledge, with high payload embedding, the significant improvement in these features (in terms of saliency, PSNR, SSIM, and NC) has not been achieved by the state-of-the-art methods. Thus, the outcomes of this research realizes a trade-off independent image watermarking method, which is a first of its kind in this domain.

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A robust salient object detection using edge enhanced global topographical saliency

Cited by 8 publications

References 46 publications

HDR image watermarking using saliency detection and quantization index modulation

HDR image watermarking using saliency detection and quantization index modulation

High payload watermarking based on enhanced image saliency detection

Trade-off independent image watermarking using enhanced structured matrix decomposition

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